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Fast temperature field generation for welding simulation and reduction of experimental effort
(2011)

The quality of welding processes is governed by the occurring induced distortions yielding an increase in production costs due to necessary reworking. Especially for more complex specimens, it is difficult to evaluate the optimal configuration of welding sequences in order to minimize the distortion. Even experienced welding operators can solve this task only by trial and error which is time and cost consuming. In modern engineering the application of welding simulation is already known to be able to analyse the heat effects of welding virtually. However, the welding process is governed by complex physical interactions. Thus, recent weld thermal models are based on many simplifications. The state of the art is to apply numerical methods in order to solve the transient heat conduction equation. Therefore, it is not possible to use the real process parameters as input for the mathematical model. The model parameters which allow calculating a temperature field that is in best agreement with the experiments cannot be defined directly but inversely by multiple simulations runs. In case of numerical simulation software based on finite discretization schemes this approach is very time consuming and requires expert users. The weld thermal model contains an initial weakness which has to be adapted by finding an optimal set of model parameters. This process of calibration is often done against few experiments. The range of model validity is limited. An extension can be obtained by performing a calibration against multiple experiments. The focus of the paper is to show a combined modelling technique which provides an efficient solution of the inverse heat conduction problem mentioned above. On the one hand the inverse problem is solved by application of fast weld thermal models which are closed form solutions of the heat conduction equation. In addition, a global optimization algorithm allows an automated calibration of the weld thermal model. This technique is able to provide a temperature field automatically that fits the experimental one with high accuracy within minutes on ordinary office computers. This fast paradigm permits confirming the application of welding simulation in an industrial environment as automotive industry. On the other hand, the initial model weakness is compensated by calibrating the model against multiple experiments. The unknown relationship between model and process parameters is approximated by a neural network. The validity of the model is increased successively and enables to decrease experimental effort, For a test case, it is shown that this approach yields accurate temperature fields within very short amount of time for unknown process parameters as input data to the model contributing to the requirement to construct a substitute system of the real welding process.

This paper presents an approach to reconstruct the three-dimensional transient temperature field for fusion welding processes as input data for computational weld mechanics. The methodology to solve this inverse heat conduction problem fast and automatically focuses on analytical temperature field models for volumetric heat sources and application of global optimisation. The important issue addressed here is the question which experimental data is needed to guarantee a unique reconstruction of the experimental temperature field. Different computational-experimental test cases are executed to determine the influence of various sets of discrete experimental data on the solvability of the optimisation problem. The application of energy distributions utilised for laser beam welding allows reconstructing the temperature field efficiently. Furthermore, the heat input into the workpiece determined by the simulation contributes to the evaluation of the thermal efficiency of the welding process.

The present thesis provides a contribution to the solution of the inverse heat conduction problem in welding simulation. The solution strategy is governed by the need that the phenomenological simulation model utilised for the direct solution has to provide calculation results within short computational time. This is a fundamental criterion in order to apply optimisation algorithms for the detection of optimal model parameter sets. The direct simulation model focuses on the application of functional-analytical methods for solving the corresponding partial differential equation of heat conduction. In particular, volume heat sources with a bounding of the domain of action are applied. Besides the known normal and exponential distribution, the models are extended by the introduction of parabolically distributed heat sources. Furthermore, the movement on finite specimens under consideration of curved trajectories has been introduced and solved analytically. The calibration of heat source models against experimental reference data involves the simultaneous adaptation of model parameters. Here, the global parameter space is searched in a randomised manner. However, an optimisation pre-processing is needed to get information about the sensitivity of the weld characteristics like weld pool dimension or objective function due to a change of the model parameters. Because of their low computational cost functional-analytical models are well suited to allow extensive sensitivity studies which is demonstrated in this thesis. For real welding experiments the applicability of the simulation framework to reconstruct the temperature field is shown. In addition, computational experiments are performed that allow to evaluate which experimental reference data is needed to represent the temperature field uniquely. Moreover, the influence of the reference data like fusion line in the cross section or temperature measurements are examined concerning the response behaviour of the objective function and the uniqueness of the optimisation problem. The efficient solution of the inverse problem requires two aspects, namely fast solutions of the direct problem but also a reasonable number of degrees of freedom of the optimization problem. Hence, a method was developed that allows the direct derivation of the energy distribution by means of the fusion line in the cross section, which allows reducing the dimension of the optimisation problem significantly. All conclusions regarding the sensitivity studies and optimisation behaviour are also valid for numerical models for which reason the investigations can be treated as generic.

Microcrack formation during gas metal arc welding of high-strength fine-grained structural steel
(2014)

The recent development of high-performance-modified spray arc processes in gas metal arc welding due to modern digital control technology and inverter power sources enables a focused spray arc, which results in higher penetration depths and welding speed. However, microcracks occurred in the weld metal while approaching the process limits of the modified spray arc, represented by a 20-mm double layer DV-groove butt-weld. These cracks were detected in structural steel exhibiting a yield strength level of up to 960 MPa and are neither dependent on the used weld power source nor a consequence of the modified spray arc process itself. The metallographic and fractographic investigations of the rather exceptional fracture surface lead to the classification of the microcracks as hot cracks. The effects of certain welding parameters on the crack probability are clarified using a statistical design of experiment. However, these microcracks do not impact the design specification for toughness in the Charpy V-notch test (absorbed energy at -40 °C for the present material is 30 J).

Life Cycle Assessment (LCA) and Social Life Cycle Assessment (SLCA) are applied in evaluating possible social and environmental impacts of the state-of-art welding technologies, such as Manual Metal Arc Welding (MMAW), Manual Gas Metal Arc Welding (GMAW), Automatic GMAW and Automatic Laser-Arc Hybrid Welding (LAHW). The LCA results indicate that for 1 meter weld seam, MMAW consumes the largest amount of resources (like filler material and coating on electrodes) and energy, which contributes to comparatively higher environmental impacts in global warming potential, acidification, photochemical ozone creation potential and eutrophication than other chosen processes. With regard to social aspects, the health issues and fair salary are under survey to compare the relative potential risk on human health caused by fumes in different welding technologies, and to indicate the sufficiency of current salary of welders in Germany. The results reflect that the wage status of welders is still fair and sufficient. The manual processes bring much higher potential risk of welders health than the automatic processes, especially MMAW.